Abstract Cardiovascular diseases (CVD) and strokes produce immense health and economic burdens globally. Coronary Artery Disease (CAD) is the most common type of cardiovascular disease. Coronary Angiography, which is an invasive approach for detection and treatment, is also the standard procedure for diagnosing CAD. In this work, we illustrate a Medical Decision Support System for the prediction of Coronary Artery Disease (CAD) using Fuzzy Cognitive Maps (FCM). FCMs are a promising modeling methodology, based on human knowledge, capable of dealing with ambiguity and uncertainty and learning how to adapt to the unknown or changing environment. The newly proposed MDSS is developed using the basic notions of Fuzzy Cognitive Maps and is intended to diagnose CAD utilizing specific inputs related to the patient’s clinical conditions. We show that the proposed model, when tested on a dataset collected from the Laboratory of Nuclear Medicine of the University Hospital of Patras achieves accuracy of 78.2% outmatching several state-of-the-art classification algorithms.

中文翻译：

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使用模糊认知图诊断冠状动脉疾病的无创建模方法

摘要 心血管疾病 (CVD) 和中风给全球带来了巨大的健康和经济负担。冠状动脉疾病 (CAD) 是最常见的心血管疾病类型。冠状动脉造影是一种侵入性的检测和治疗方法，也是诊断 CAD 的标准程序。在这项工作中，我们说明了使用模糊认知图 (FCM) 预测冠状动脉疾病 (CAD) 的医疗决策支持系统。FCM 是一种很有前途的建模方法，基于人类知识，能够处理模糊性和不确定性，并学习如何适应未知或不断变化的环境。新提出的 MDSS 是使用模糊认知图的基本概念开发的，旨在利用与患者临床状况相关的特定输入来诊断 CAD。